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Research, Vision Expertise

350k – 475kSan Francisco, CAML EngineeringOnsite
Summary

Conducts research on visual perception, multimodal learning, and large-scale AI model training. Designs architectures, builds datasets and evaluations, and collaborates on frontier models. Requires ML expertise, Python proficiency, and experimental rigor.

About the role

What You’ll Do

  • Own research projects on training and performance analysis of multimodal AI models.
  • Curate and build large-scale datasets and evaluation benchmarks to advance vision capabilities.
  • Work with our data infrastructure engineers, pretraining researchers and engineers, and product team to create frontier multimodal models and the products that leverage them.
  • Publish and present research that moves the entire community forward. Share code, datasets, and insights that accelerate progress across industry and academia.

Skills and Qualifications

Minimum qualifications:

  • Ability to design, run, and analyze experiments thoughtfully, with demonstrated research judgment and empirical rigor.
  • Understanding of machine learning fundamentals, large-scale training, and distributed compute environments.
  • Proficiency in Python and familiarity with at least one deep learning framework (e.g., PyTorch, TensorFlow, or JAX). Comfortable with debugging distributed training and writing code that scales.
  • Bachelor’s degree or equivalent experience in Computer Science, Machine Learning, Physics, Mathematics, or a related discipline with strong theoretical and empirical grounding.
  • Clarity in communication, an ability to explain complex technical concepts in writing.

Preferred qualifications:

  • Research or engineering contributions in visual reasoning, spatial understanding, or multimodal architecture design.
  • Experience developing evaluation frameworks for multimodal tasks.
  • Publications or open-source contributions in vision-language modeling, video understanding, or multimodal AI.
  • A strong grasp of probability, statistics, and ML fundamentals. You can look at experimental data and distinguish between real effects, noise, and bugs.
  • PhD in Computer Science, Machine Learning, Physics, Mathematics, or a related discipline with strong theoretical and empirical grounding; or, equivalent industry research experience.

Logistics

Compensation: Depending on background, skills and experience, the expected annual salary range for this position is $350,000 - $475,000 USD.

Benefits: Generous health, dental, and vision benefits, unlimited PTO, paid parental leave, and relocation support as needed.

Skills
PyTorchTensorFlowJAXPythonMachine LearningMultimodal AIVision-Language ModelsDistributed TrainingLarge-Scale DatasetsEvaluation Frameworks
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